Software Engineer, Infranomics

ABOUT THE TEAM The Infranomics team builds the software and data foundations that help OpenAI understand, plan, and improve the economics of its infrastructure. The team works across engineering and finance to make infrastructure spend visible, allocate capacity effectively, and improve efficiency as our products grow. Our systems support the CPU, network, storage and GPU infrastructure behind products such as ChatGPT, the API, and Codex. We are expanding these foundations to connect resource usage, cost, forecasting, and planning so teams can make better decisions at scale.   ABOUT THE ROLE We are looking for a Software Engineer to lead the design, implementation, and operation of systems for infrastructure cost and efficiency. You will build the platforms that explain where infrastructure spend goes, identify opportunities to improve utilization, and help teams plan the capacity they need. We ideally want direct experience building and operating software for infrastructure economics, such as usage metering, cost attribution, resource efficiency, budgeting, forecasting, or capacity planning. You should have owned systems that connect compute, storage, or network consumption to cost and help teams make measurable efficiency and investment decisions. You will set technical direction for a growing area while staying close to the code. Working with infrastructure engineers, product teams, finance, and leadership, you will turn ambiguous business and engineering problems into reliable software, shared data, and measurable improvements. This role offers substantial autonomy and the opportunity to shape how OpenAI manages its infrastructure investment. This role is based in San Francisco, CA. This is an on-site role.   IN THIS ROLE, YOU WILL: - Define the technical direction and roadmap for infrastructure cost and efficiency systems, and lead projects from problem definition through implementation, adoption, and ongoing operation. - Build billing, usage metering, and cost attribution systems that connect infrastructure spend to resources, workloads, services, and the teams that own them. - Develop data pipelines and shared data models that combine cloud billing, resource inventory, and utilization signals into a dependable view of cost and capacity. - Build tools for budgeting, forecasting, and capacity planning that help teams anticipate demand, allocate resources, and inform procurement decisions. - Identify underutilized resources and other sources of waste, then partner with engineering teams to deliver and measure improvements while preserving performance and reliability. - Create APIs, reporting tools, and automated controls that help teams understand their consumption, manage budgets, and make informed infrastructure tradeoffs. - Provide technical leadership across teams, mentor engineers, and own the correctness, scalability, and production behavior of the systems you build. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have over 7 years of experience designing, building, and operating production software and distributed systems, with technical ownership across multiple teams or a significant infrastructure domain. - Have built systems for infrastructure efficiency, cloud cost attribution, usage metering, budgeting, forecasting, or capacity management, and can connect that work to measurable outcomes. - Remain a hands-on engineer who can move between architecture, implementation, debugging, and operational improvements. - Understand how compute, storage, and networking consumption translate into cost, and can reason about the tradeoffs among utilization, performance, reliability, and growth. - Care deeply about data correctness and can build trustworthy systems from complex billing and operational data. - Work effectively across engineering, finance, product, and leadership, translating broad goals into a clear plan and driving adoption without relying on formal authority. - Thrive with substantial autonomy, take ownership of loosely defined problems, and make pragmatic decisions as requirements evolve. - Have experience building internal platforms that give engineering teams visibility into cloud spend, resource utilization, and ownership. - Have experience developing batch or streaming data pipelines, financial data platforms, or large-scale analytics systems. - Have experience with Kubernetes, public cloud infrastructure, or resource management systems across cloud and on-premises environments. - Have experience automating resource allocation, cost allocation policies, budget tracking, or capacity forecasting. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.  We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. 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